A novel particle filtering method for estimation of pulse pressure variation during spontaneous breathing

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dc.contributor.authorKim, Sunghan, 1975-
dc.contributor.authorNoor, Fouzia
dc.contributor.authorAboy, Mateo
dc.contributor.authorMcNames, James
dc.date.accessioned2016-08-25T13:20:17Z
dc.date.available2016-08-25T13:20:17Z
dc.date.issued2016-08-11
dc.date.updated2016-08-11T16:03:05Z
dc.description.abstractBackground: We describe the first automatic algorithm designed to estimate the pulse pressure variation (PPVPPV) from arterial blood pressure (ABP) signals under spontaneous breathing conditions. While currently there are a few publicly available algorithms to automatically estimate PPVPPV accurately and reliably in mechanically ventilated subjects, at the moment there is no automatic algorithm for estimating PPVPPV on spontaneously breathing subjects. The algorithm utilizes our recently developed sequential Monte Carlo method (SMCM), which is called a maximum a-posteriori adaptive marginalized particle filter (MAM-PF). We report the performance assessment results of the proposed algorithm on real ABP signals from spontaneously breathing subjects. Results: Our assessment results indicate good agreement between the automatically estimated PPVPPV and the gold standard PPVPPV obtained with manual annotations. All of the automatically estimated PPVPPV index measurements (PPVautoPPVauto) were in agreement with manual gold standard measurements (PPVmanuPPVmanu) within ±4 % accuracy. Conclusion: The proposed automatic algorithm is able to give reliable estimations of PPVPPV given ABP signals alone during spontaneous breathing.en_US
dc.identifier.citationBioMedical Engineering OnLine. 2016 Aug 11;15(1):94en_US
dc.identifier.doi10.1186/s12938-016-0214-x
dc.identifier.urihttp://dx.doi.org/10.1186/s12938-016-0214-x
dc.identifier.urihttp://hdl.handle.net/10342/5876
dc.language.isoen_USen_US
dc.language.rfc3066en
dc.relation.urihttp://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-016-0214-xen_US
dc.rights.holderThe Author(s)
dc.subjectExtended Kalman filteren_US
dc.subjectA-posteriori distributionen_US
dc.subjectMaximum a-posteriori estimationen_US
dc.subjectMarginalized particle filteren_US
dc.subjectMulti-harmonic signalen_US
dc.titleA novel particle filtering method for estimation of pulse pressure variation during spontaneous breathingen_US
dc.typeArticleen_US
ecu.journal.issue1en_US
ecu.journal.nameBioMedical Engineering OnLineen_US
ecu.journal.pages94en_US
ecu.journal.volume15en_US

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